code: def rrse(actual, predicted):
      """Root Relative Squared Error.
  
      Args:
          actual (np.ndarray): The actual value.
          predicted (np.ndarray): The predicted value.
  
      Returns:
          float: The root relative square error between the actual and the
              predicted value.
  
      """
      return np.sqrt(
          np.sum(np.square(actual - predicted))
          / np.sum(np.square(actual - np.mean(actual)))
      )
  
file_path: garage/src/garage/np/_functions.py
imports: import warnings
  import numpy
  import scipy.signal
label_desc: Use image node_id 2 for calling a global function with example usage: rrse(actual, predicted) and returns: np